Required Packages

  • dplyr was used to manipulate the data
  • ggplo2 was used to create figures
  • tidyr was not used since the data was already arranged to desired standards
library(dplyr)
library(ggplot2)

What is a Mantis Shrimp?

  • Mantis shrimps or stomatopods
  • Marine crustaceans of the order Stomatopoda
  • Some species have blunt forelimbs while others have sharp ones

External Anatomy

  • Appendages
  • Telson

Telson Sparring

  • During telson sparring, mantis shrimp take turns striking with their appendages against the telson of their opponent
  • Individuals direct nearly every strike to the telson, and this is facilitated by the recipient assuming a coiled position referred to as a ‘telson coil’

Data used

data_1 <- read.csv("https://ndownloader.figshare.com/files/16851587")
knitr::kable(data_1[1:5,1:3])
species appendage mass
falcatus smasher 0.24
falcatus smasher 0.93
falcatus smasher 0.30
falcatus smasher 1.12
falcatus smasher 1.20

What does this data describe? (Prose)

Mantis Shrimp Shells

  • Many types of animals develop morphological traits to partake in ritualized combat.
  • Mantis shrimp present an interesting case in which their unique form of ritualized combat, termed telson sparring, may have coevolved with specialized morphological armour.

What is COR?

  • The coefficient of restitution (COR), also denoted by (e), is the ratio of the final to initial relative velocity between two objects after they collide

  • can also be viewed in terms of kinetic energy before and after a collision.

  • e is usually a positive number between 0 and 1:

  • e = 0: This is a perfectly inelastic collision. Kinetic energy is dissipated (converted to heat or work).

  • 0 < e < 1: This is a real-world inelastic collision, in which some kinetic energy is dissipated.

  • e = 1: This is a perfectly elastic collision, in which no kinetic energy is dissipated, and the objects rebound from one another with the same initial velocity.

Data Manipulation

  • separated species with "smasher" and "spearer" appendages by using filter()
  • Wanted to see if there were different trends between appendage types
smasher_data <- data_1 %>%
  group_by(appendage) %>%
  filter(appendage == "smasher") 

spearer_data <- data_1 %>%
  group_by(appendage) %>%
  filter(appendage != "smasher")

Linear Model Function

lm_1 <- lm(cor.telson~cor.abdomen, data_1) #linear model function 
summary(lm_1)[[9]] #number assocaited with chunk, returns r squared value
## [1] 0.1009381
results <- summary(lm_1) 
results$coefficients[8] #returns p value
## [1] 0.001330482

Figure 1 - Plot of all appendage types

## [1] 0.1009381
## [1] 0.001330482

Figure 2 - Plot of smashers

## [1] 0.03652613
## [1] 0.06009676

Figure 3 - Plot of spearers

## [1] -0.0254198
## [1] 0.4669373

Thank you